FPGA-Driven Execution Stacks Slash Latency by 71% as Agentic AI Demands Speed

Leading trading technology providers leverage FPGA acceleration and kernel-bypass networking to deliver ultra-low latency, a critical differentiator for the burgeoning agentic AI trading landscape.

Tradesnaut Quant Research Desk · September 27, 2026 · 6 min read · Agentic AI & Trading

FPGA-Driven Execution Stacks Slash Latency by 71% as Agentic AI Demands Speed

Key takeaways

Trading desks are aggressively adopting FPGA-accelerated systems and kernel-bypass networking to push execution latency into the nanosecond range.
The surge in agentic AI trading amplifies the need for ultra-low latency infrastructure, shifting the competitive edge from pure network speed to optimized processing within the trading stack.
Continued innovation in smart NICs and hardware-accelerated trading engines, alongside scalable AI infrastructure from major tech players, will define future performance gains and market leadership.

What changed

The race for speed on global execution desks has entered a new phase, driven by the imperative to service sophisticated agentic AI trading strategies. Firms are increasingly turning to Field-Programmable Gate Arrays (FPGAs) and kernel-bypass networking to achieve critical latency reductions. In a significant development, Exegy announced in April 2026 that enhancements to its nxAccess FPGA-based trading engine delivered an impressive 71% reduction in execution-stack latency by enabling dynamic switching to the fastest available exchange session and private links in real-time. This follows Exegy's January 2026 acquisition of NovaSparks Inc., which further strengthened its FPGA solutions for mission-critical electronic trading platforms. Similarly, AMD's Solarflare X4 Ethernet Adapters are gaining traction, promising up to 40% lower latency than previous generations and 200% improved system performance compared to its Solarflare X2 series, according to an October 2025 announcement. These hardware advancements are directly addressing the ultra-low latency demands of high-frequency trading, where top firms now target tick-to-trade times under 500 nanoseconds using FPGA technology. On the software front, technologies like Data Plane Development Kit (DPDK) continue to be critical, enabling applications to bypass the operating system kernel and directly access network cards, reducing kernel-contributed latency from 20-50 microseconds to a mere 1-5 microseconds. This intensified focus on nanosecond precision is a direct response to the rollout of agentic AI capabilities by fintechs like Public, Robinhood, and Gemini throughout 2026, which allow AI to autonomously monitor markets and execute trades based on user-defined strategies.

The mechanism

Achieving ultra-low latency in modern trading hinges on circumventing the traditional processing overhead inherent in conventional operating systems. Kernel-bypass techniques like DPDK achieve this by giving trading applications direct access to the network interface card's (NIC) receive and transmit queues. This involves mapping the NIC's memory directly into the application's address space and dedicating CPU cores to continuously poll these queues, thereby eliminating the significant delays introduced by kernel context switching and layered network stacks. While effective, this approach trades CPU efficiency for raw speed, as polling cores consume full CPU cycles even when idle. FPGAs further accelerate this by implementing critical market data processing and order execution logic directly in hardware. This purpose-built architecture eliminates software latency and offers deterministic performance, even under heavy market load. Firms like Exegy are integrating market data processing and execution into a single FPGA-accelerated workflow, essentially collapsing the path from data to decision to execution. The challenge, however, is that as network latency is optimized, the bottleneck often migrates downstream to other parts of the trading system, such as the order processor, a shift that requires continuous architectural reassessment. The relentless pursuit of this 'tick-to-trade' efficiency is now paramount for agentic AI, which relies on these rapid decision-making cycles to capture fleeting market opportunities, whether through proprietary algorithms or the burgeoning retail-accessible AI agents.

Who is exposed

Companies heavily reliant on high-speed market access and those providing the underlying infrastructure are most exposed to these trends. Virtu Financial (VIRT), a prominent global market maker, is a clear beneficiary of advancements in low-latency technology. Virtu leverages cutting-edge technology to deliver liquidity to global markets, and the firm reported strong preliminary Q2 2026 results, with net income of 84.9 million and total revenues of

,190.0 million, an increase of 19.0% year-over-year. Virtu shares have risen 54.74% over the last year. Network equipment providers also play a critical role. Cisco Systems (CSCO) is actively expanding its AI infrastructure footprint, with expected AI infrastructure orders from hyperscalers reaching $4 billion in fiscal 2026, according to a May 2026 report. Cisco's strategy involves providing high-performance networking products across various customer segments, and the company projects fiscal 2026 revenue of $62.8 billion to $63.0 billion. CSCO shares have gained 61.79% over the past year. Interactive Brokers (IBKR), while not an HFT firm, is critical as an 'infrastructure bridge' for institutional-grade execution to a broader client base, including hedge funds and professional traders. Its SmartRouting technology aims for superior price improvement and leverages significant equity capital. IBKR shares have seen a 39.02% increase over the last year. The global agentic AI market, estimated at US$9.87 billion in 2026, is projected to grow to US

14.89 billion by 2033, creating a massive demand for optimized hardware and software.

Quantitative Outlook

The market data underscores the performance of firms at the forefront of leveraging advanced trading infrastructure. Virtu Financial, Inc. (VIRT) is trading at 53.40, marking a 1.41% increase today. Over the past year, VIRT has seen a substantial 54.74% rise, indicating strong investor confidence in its technology-driven market-making model. This performance aligns with its reported Q2 2026 net income of 84.9 million and total revenues of

,190.0 million, reflecting the continued importance of speed and efficiency. Cisco Systems (CSCO), a key enabler of the networking backbone for high-speed and AI-driven trading, is currently at 106.70. While down slightly by 0.25% today, its one-year performance of 61.79% suggests strong demand for its AI-ready network infrastructure and high-performance products, particularly given its raised fiscal 2026 revenue guidance. Interactive Brokers Group (IBKR) trades at 89.24, down 0.65% today, but boasts a 39.02% gain over the last year. This performance highlights its strategic position in providing sophisticated trading access and its recognition of AI's growing influence on investment opportunities. The broader market, represented by the S&P 500 at 7,743.41 (+0.51%) and NASDAQ at 27,069 (+0.48%), shows a general positive trend. A shift in this picture could occur if regulatory bodies impose new requirements on latency or AI agent autonomy, increasing compliance costs. Conversely, continued advancements in silicon photonics and co-packaged optics, as discussed by NVIDIA's collaboration with TSMC on CPO technology, could offer further latency reductions and expand the addressable market for these high-performance solutions.

Tags: FPGA, Kernel Bypass, Latency Optimization, Agentic AI, High-Frequency Trading